The deal is valued at $5.375 billion and overrides the previously announced plan to spin-off the robotics business as a separately listed company.

“SoftBank’s offer…reflects the long-term strengths of the division, and the divestment will create immediate value to ABB shareholders. Our ambitions for ABB are unchanged, and we will continue to focus on our long-term strategy, building on our leading positions in electrification and automation,” said Peter Voser, chairman of ABB, in a release.

The transaction is subject to regulatory approvals and other closing conditions and is expected to close by late 2026.

 “SoftBank’s next frontier is physical AI. Together with ABB Robotics, we will unite world-class technology and talent under our shared vision to fuse artificial super intelligence and robotics, driving a groundbreaking evolution that will propel humanity forward,” said Masayoshi Son, chairman and CEO of SoftBank Group Corp.

As part of the divestment, Sami Atiya, president of the Robotics and Discrete Automation business area and member of the executive committee, will leave ABB by the end of 2026.

“I am convinced that with the acquisition by SoftBank our robotics business will be in excellent hands, creating a platform for growth that will benefit from the numerous opportunities in automation and AI that we are seeing across many industries and geographies,” said Atiya.

ABB will adjust its reporting structure and move to three business areas. As of the fourth quarter 2025, the Robotics division will be reported as discontinued operations. At the same time, the machine automation division, which together with ABB Robotics currently forms the Robotics and Discrete Automation business, will become a part of the Process Automation business.

Upon closing, the divestment will result in a non-operational pre-tax book gain of approximately $2.4 billion with expected cash proceeds of approximately $5.3 billion. The expected separation costs related to the divestment are approximately $200 million, about half of which was already included in its 2025 guidance. ABB’s current best estimate of the transaction-related cash tax outflows in respect of the local business carve-out is in the range of $400 – $500 million.

While ABB Robotics is a leader in its industry, the company has previously stated there are limited business and technology synergies between the ABB Robotics business and the remainder of ABB’s businesses, with different demand and market characteristics. The ABB Robotics division has a workforce of approximately 7,000 with 2024 revenues of $2.3 billion.

Editor’s note: RoboBusiness 2025, which takes place Ocxtober 15-16 in Santa Clara, Calif., will feature tracks on physical AI, design and development, enabling technologies, business, field robotics, and humanoids.

Ali Raja, managing director of automation for industries, and Thomas-Tianwei Wang, lead AI application engineer at ABB Robotics, will be among the speakers. Register now to attend.

The post ABB sells robotics division to SoftBank Group for $5.3B appeared first on Engineering.com.

ABB Robotics has added AI capability to its Robotstudio Suite, an offline programming and simulation tool for robotic applications.

The product was launched at the China International Industry Fair in Shanghai.

The new Robotstudio AI Assistant uses generative Al to make robot programming faster, easier, and more accessible. ABB Robotics president Marc Segura says this is the company’s latest effort to commercialize AI by enhancing robot versatility and encouraging their use beyond traditional manufacturing.

“The demand for AI in robotics is driven by the need for greater flexibility; faster commissioning cycles and a shortage of the specialist skills traditionally needed to program and operate robots. By adding this generative AI Assistant, we are expanding its benefits to reach less experienced users and help experts solve technical challenges faster,” Segura says.

Featuring a Large Language Model (LLM) that understands and interprets human language, Robotstudio AI Assistant draws from ABB’s library of manuals and documentation to deliver accurate responses to questions, enabling users to set up faster and quickly find answers to technical challenges.

Robotstudio is more than a straightforward LLM, however. Magnus Seger, Global Product Manager, Simulation Software, ABB Robotics, says it also has “agentic” qualities because it and autonomously selects from and uses multiple tools, depending on the user’s request.

The AI assistant scans and queries ABB manuals using a retrieval augmented generation (RAG) system. It also reads robot code from the user’s active RobotStudio project to ground answers in the user’s own code, making it more applicable to their specific enquiry and task.

Seger says that beyond the select product manuals and the user’s local project, no external data is accessed.

“The model itself is trained using selected manuals (RobotStudio, RobotWare, RAPID) that are made available via a RAG system. ABB’s documents include current, leading-edge information that best fits challenges relating to ABB Robots,” says Seger. “ABB’s document library is updated regularly, and new documents are created alongside each new robotics launch, which is why using this model gives users information that is up-to-the-minute and retrieves the latest technology documentation at runtime.”

Queries are handled through the Azure-hosted RAG system and data is transmitted to the Azure cloud using encryption. Customer-provided data is only used for the active request and never for training.

“The safety of our customers’ data is very important to us; our protocols for storing data are reviewed and updated regularly, in line with current best practice and the ABB library is not locally stored each time there is an interaction with RobotStudio,” Seger says.

It’s important to note this is truly an assistant. ABB’s AI assistant will not program a robot autonomously with no user interaction, and users can’t train the AI to do so.

“Both RobotStudio and RobotStudio AI Assistant currently require user involvement, and any code suggestions must be reviewed and approved by the user before being applied to a robot controller, cautions Seger. “However, RobotStudio AI Assistant is part of ABB Robotics Autonomous Versatile Robotics (AVR) portfolio, as it supports ABB robots and software to move closer to versatility and intelligence by enabling them to develop skills that include planning, adapting, and executing diverse tasks, independently, in real time, and without human intervention.”

The post ABB’s new Robotstudio AI assistant helps program robots appeared first on Engineering.com.

The ANSI/A3 R15.06-2025 American National Standard for Industrial Robots and Robot Systems – Safety Requirements is now available and A3 says it marks the most significant advancement in industrial robot safety requirements in more than a decade.

“Publishing this safety standard is perhaps the most important thing A3 can do, as it directly impacts the safety of millions of people working in industrial environments around the world,” said Jeff Burnstein, president of A3, in a release.

This standard is available in protected PDF format and includes:
Part 1: Safety requirements for industrial robots
Part 2: Safety requirements for industrial robot applications and robot cells
Part 3: Will address safety requirements for users of industrial robot cells. It’s expected to be published later this year. Once available, it will be retroactively provided at no additional cost to anyone who purchases the full standard.

R15.06 is the U.S. national adoption of ISO 10218 Parts 1 and 2 and is a revision of ANSI/RIA R15.06-2012, which was launched by the Robotic Industries Association (RIA) before it became part of A3.

Key changes in ANSI/A3 R15.06-2025 include:

• Clarified functional safety requirements that improve usability and compliance for manufacturers and integrators
• Integrated guidance for collaborative robot applications, consolidating ISO/TS 15066
• New content on end-effectors and manual load/unload procedures, derived from ISO/TR 20218-1 and ISO/TR 20218-2
• Updated robot classifications, with corresponding safety functions and test methodologies
• Cybersecurity guidance included as part of safety planning and implementation
• Refined terminology, including the replacement of “safety-rated monitored stop” with “monitored standstill” for broader technical accuracy

“This standard delivers clearer guidance, smarter classifications, and a roadmap for safety in the era of intelligent automation,” said Carole Franklin, director of standards development, robotics at A3. “It empowers manufacturers and integrators to design and deploy safer systems more confidently while supporting innovation without compromising human well-being.”

The post Robot safety standard gets fresh update appeared first on Engineering.com.

Mechatronics blends mechanical engineering, electronics, control systems, and computing into one intelligent system. Without it, self-parking cars, smart thermostats, and precision robotics simply won’t work reliably in the real world. This blend of mechanical systems, electronics and software has blurred the lines between traditional engineering disciplines, especially with the rapid and ongoing development of artificial intelligence.

Dr. Hoe Seng Ooi, Chief Technology Officer at Taipei-based NexAIoT, thinks that mechatronics is the key to unlocking “physical AI” on the street and in our homes, and he joins Jim Anderton on the podcast to explain why.

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The report says North American companies ordered 17,635 robots valued at $1.094 billion in the first six months of 2025. Automotive OEMS led with a 34% year-over-year increase in units ordered. Other top-performing segments included plastics and rubber (+9%) and life sciences/pharma/biomed (+8%).

In Q2, companies ordered 8,571 robots worth $513 million, marking a 9% increase in units compared to Q2 2024. Life sciences/pharma/biomed posted the strongest sector growth in the quarter (+22%), followed by semiconductors/electronics/photonics (+18%) and steady gains in plastics, automotive components, and general industry.

 “It’s not just about efficiency anymore. It’s about building resilience, improving flexibility, and staying competitive in a rapidly changing global market. If these patterns hold, the North American robotics market could outperform 2024 levels by mid-single digit growth rates by the end of the year,” said Alex Shikany, Executive Vice President at A3.

Cobots’ rising influence

Collaborative robots (cobots) accounted for a growing share of the market with 3,085 units ordered in the first half of 2025, valued at $114 million. In Q2, cobots made up 23.7% of all units and 14.7% of revenue. These systems work safely alongside humans and address automation needs in space- or labor-constrained environments. A3 began tracking cobots as a distinct category in Q1 2025 and will expand future reporting to include growth trends by sector.

Automotive versus non-automotive sectors

The non-automotive sector took the lead over automotive in Q2, accounting for 56% of total units ordered. This move reflects the expanding role of automation in industries such as life sciences, electronics, and other non-automotive manufacturing sectors.

The post Report shows steady automation investment in first half of 2025 appeared first on Engineering.com.

After the wildfires burned thousands of acres, destroying homes, infrastructure, and natural habitats, this initiative will deploy the microfactory in Pacific Palisades, California, to build modular structures onsite, offering a glimpse into the future of affordable housing construction.

Watch the video on youtube.

“Together, Cosmic and ABB Robotics are rewriting the rules of construction and disaster recovery,” said Marc Segura, President of ABB Robotics Division. “By integrating our robots and digital twin technologies into Cosmic’s AI-powered mobile microfactory, we’re enabling real-time, precision automation ideal for remote and disaster-affected sites.”

These microfactories integrate ABB’s IRB 6710 robots and RobotStudio digital twin software with Cosmic’s Robotic Workstation Cell and AI-driven Building Information Model (BIM) – an end-to-end platform that handles design, permitting, procurement, robotic fabrication and assembly.

Housed within an on-site microfactory, these systems fabricate custom structural wall panels with millimeter precision just-in-time for assembly at the construction site.

Cosmic uses ABB’s RobotStudio with its AI BIM allowing the entire build process to be simulated and optimized in a digital environment before deployment. Once on location, Cosmic’s AI and computer vision systems work with the robots, making real-time decisions, detecting issues, and ensuring consistent quality.

These homes are built with non-combustible materials, solar and battery backup systems, and water independence through greywater recycling and renewable water generation. Each home exceeds California’s wildfire and energy efficiency codes. By delivering a turnkey experience from permitting to final construction, Cosmic is redefining what’s possible in emergency recovery.

Cosmic says its mobile microfactory reduces construction time by up to 70% and lowers total building costs by approximately 30% compared to conventional methods. Homes can be delivered in just 12 weeks at $550–$700 per square foot, compared to Los Angeles’ typical $800–$1,000 range.

“Our mobile microfactory is fast enough for disaster recovery, efficient enough to drastically lower costs, and smart enough not to compromise on quality,” said Sasha Jokic, Founder and CEO of Cosmic Buildings. “By integrating robotic automation with AI reasoning and on-site deployment, Cosmic achieves construction speeds three times faster than traditional methods, completing projects in as little as three months.”

The post AI and robotics-powered microfactory rebuilds homes lost to the California wildfires appeared first on Engineering.com.

In 1962, an animated sitcom debuted on television called the Jetsons. It predicted a future with extensive automation of every aspect of life, from cleaning the floors to operating factories. Much of it has come true, with extensive robotic operation now commonplace in manufacturing, supply chain services and increasingly, in medicine. But that humanoid robot as personal servant remains elusive. Why?

The Robot Report’s Editorial Director, Eugene Demaitre, tracks automation industry trends in industrial, commercial and residential applications and he discussed the current state-of-the-art, and future prospects including those of humanoid personal assistants, in conversation with engineering.com’s Jim Anderton. 

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UR Studio was showcased at the UR booth at the Automatica trade fair in Munich. The company says it enables integrators to build 1:1 online simulations of their work cell and simulate every key aspect of its setup. Users can test robot movements, simulate reach, speed and workflow, and calculate cycle time.

“Whether you are new to automation or an experienced customer optimizing a complex cell, you want assurance and certainty before making the final decision on your solution,” says Tero Tolonen, Universal Robots’ Chief Product Officer. “With UR Studio, we now provide an intuitive, easy-accessible tool to simulate and visualize the end-user setup and thoroughly test the cell and its capabilities – mapping out details for maximum efficiency and performance.”

UR Studio interacts with UR’s robot portfolio and various components, such as pallets, machines, workpieces and end effectors—including standard grippers often used with UR cobots. Items can be configured to the user’s preferences with the option of importing elements to mimic the workspace. This ensures the final solution fits within the real-world environment and allows for potential issues to be identified early.

Surprisingly, UR Studio is free of charge and runs directly on desktop browsers requiring no installation—simply log into the UR Studio website to get started. Its intuitive interface makes navigation of the simulated environment effortless. It’s preloaded with templates for the most common applications such as machine tending, screwdriving, palletizing and pick-and-place. UR says new application templates will be added continuously.

UR Studio will initially be available in English, but will soon be released in German, Spanish, Chinese (simplified) and Japanese.

The post Universal Robots launches UR Studio appeared first on Engineering.com.

First, the disconnect between innovation and production is exacerbating the problem of inadequate workforce development, where training and skills development initiatives are not aligned with industry needs.

Additionally, U.S. manufacturers aren’t just struggling with a talent shortage; they’re also having problems retaining that much-needed talent to embed and finesse the necessary practices for scalable automation in advanced manufacturing.

Finally, SME manufacturers are still playing catch-up in the automation race. Without technologically empowered SMEs, the wider U.S. manufacturing industry will fail to progress at the same rate as Asian manufacturers.

That being said, there are lessons to be learned from Asian manufacturers in adopting a human-centric approach to automation. However, it’s important to adopt these learnings while keeping cultural and local workforce realities in mind.

Lessons from Asia

Many Asian manufacturers are familiar with the fact that know-how is just as important as the technology itself. The workforce has spent decades persistently refining skills alongside technology adoption.

Countries like Japan are renowned for their extremely loyal workforce and ongoing strong belief in the benefits of lifetime employment. This is why approaches like Kaizen have proven to be effective in Asian manufacturing organizations. The cultural outlook on lifetime employment within an organization has created the foundations for deep skills development and close knowledge transfer between mentors and trainees. There’s a significant emphasis on talent retention and technology integration that is carefully centralized around the human role.

Arguably, because of this, Asian manufacturers are keenly aware that automation isn’t necessarily always the answer. It’s important to know what to automate and where it makes sense to do so.

These systems have helped Asian manufacturers map out where to upskill and have been a key driver in many of them leading the way for innovation and automation in the manufacturing industry. In fact, a 2023 report from financial institution Citigroup estimates Asia tends to adopt technology eight to 12 years faster than their Western counterparts.

Why this doesn’t directly translate to the U.S.

The U.S. workforce behaves very differently. Turnover tends to be much higher, especially as younger workers who make up most of the workforce typically stay in a job for a handful of years. Additionally, career growth is more valued among U.S. workers than loyalty, especially given that long-term loyalty often goes unrecognized—unlike in Japan—making it a prime motivator to change companies.

The disconnect between training and real-world industry needs is slowing technology adoption. Many companies don’t have the skilled talent to effectively implement automation at scale, dealing with poor data use and inconsistent processes. For example, installing computer vision sensors without trained staff to interpret the data often results in wasted investment and limited impact.

This makes it more difficult for organizations to devote the time and energy to in-depth knowledge sharing and skills development alongside technology adoption. 

Propelling training and growth

It’s vital for manufacturers to build a bank of easily accessible knowledge that can be captured and transferred seamlessly. Technology has a powerful role to play in facilitating knowledge transfer and accelerated innovation via on-the-job training.

On-the-fly manuals based on real-time data capture via IoT tools can facilitate direct and smooth sharing of instructions while making sure workers are sticking to a clear procedure. Built-in sensors and other embodied AI features help monitor actions and can be useful in alerting teams to any risks or errors.

Agentic AI has a powerful role to play in multiple areas, whether it’s ensuring the continued transfer of valuable knowledge from prior experience or answering on-the-job questions that can guide less experienced employees. Voice communication with real-time video feed has a dual benefit of increasing both operator and supervisor productivity.

These data-powered solutions also mean that U.S. manufacturers can build knowledge banks that remain within their organizations after people leave. It slashes the burden on already limited human resources while still facilitating in-depth, hands-on training. Organizations can also use AI-powered platforms to design training plans that not only set clear paths of growth for employees but also ensure they align with specific business and wider industry needs.

These training methods should also promote accountability when using technology. Workers can be familiarized with data handling and hygiene and know what to look out for when data isn’t being processed properly. Easily accessible manuals also ensure teams are sticking to security protocols and understand key steps when a breach happens.

Innovating traditional methods with technology

While emerging tools like agentic AI are becoming increasingly more autonomous, the human touch can’t be completely eliminated from the picture, especially for embedding best practices around technology and scaling these. The ultimate responsibility for actioning decisions and strategies sits on people’s shoulders, not AI tools.

Yet that’s not to say that technology doesn’t have a role in empowering manufacturing teams to make better, more informed decisions—and act on these more effectively. For instance, integrating embodied AI like robots and live sensors can help streamline data capture, a fundamental component of informed decision-making and strategizing. These embodied AI tools can be used alongside powerful algorithms and ML solutions to produce accessible insights from a huge swathe of data, which speeds up the decision-making process.

AI can also boost safety on the factory floor. Robots and computer vision can monitor spaces and alert teams to risks or incidents when they occur, while reminding them of safety protocols. They can also notify staff when a failure occurs or there’s an issue with a product. This can be extremely cost- and time-effective for manufacturers. Tools like these, working alongside the human eye, can reduce the number of defective products.

For the U.S. to rival Asian manufacturers in the automation race, it needs to embrace the human role in manufacturing and facilitate faster knowledge-sharing by reinvigorating training and reskilling with technology. Ultimately, it’s not about replacing people across the board with automation, but achieving synergy between the two for accelerated yet responsible innovation at scale.

Shin Nakamura, is a Japanese manufacturing leader, President of one to ONE Holdings and President of Daiwa Steel Tube Industries, which has facilities in Japan, Vietnam, India and the U.S.

The post Lessons from Asia for successfully scaling automation appeared first on Engineering.com.

Robot path planning is a complex, with most workcells using multiple robots requiring tedious work to create interference zones and interlock signals that ensure there are no collisions during manufacturing.

Manually validating the mechanical design, planning robot paths, determining sequencing to hit optimal cycle time targets, and defining those interlocks can take a team well over 100,000 hours for a single project. This complexity often leads to failures in hitting cycle time targets, adding significant rework.

Resolver works by selecting and testing potential solutions tens to thousands of times faster than a human programmer. The goal is to quickly generate optimal, collision-free motion paths and interlock signals. This can accelerate workcell design from months to days.

The company says Resolver is essentially infinitely scalable robotic simulation power that can used to reduce the time required for many tasks, including:

• Generating accurate proposals
• Designing optimal tools and fixtures
• Producing optimal robot programs
• Adjusting for as-built deviations during commissioning
• Assessing and minimizing the impact of product design changes

“It is widely understood that the future of the manufacturing industry lies in robotics and automation. However, that future is slow to materialize because of the outdated, time-consuming, and inefficient processes commonplace in the industry,” said Peter Howard, CEO of Realtime Robotics. “Few manufacturers have the time or resources needed to enact real change. We’ve engineered Resolver to help manufacturers improve their engineering, programming and production processes – and drive greater value from their current and future investments in robots.”

How it works

Realtime Robotics’ Resolver supports path planning with any number of robots, at any phase of the workflow, generating results in minutes. The solution requires minimal onboarding and currently allows users to work directly within Siemens Process Simulate. Support for other leading simulation platforms will be rolled out later in the year, enabling teams to work directly within their preferred simulation tool.

“Resolver has the computational power to generate better motion paths than human programmers in both simple and complex workcells,” added Howard. “This is because Resolver searches the possibilities open to robotic arms, while humans tend to stay within the possibilities of the human arm.”

Users upload the workcell information, configure their sequencing and conditions, and execute a run. In minutes, Resolver will generate motion paths—including interlocks. The longer Resolver runs, the more options it provides, shortening the cycle time until the desired outcome is reached. The paths and interlocks can then be easily imported back into the simulation software for validation and operation.

Beyond determining optimal motion plans and interlocks, Resolver can help with fixture design, reachability validation, target sequencing, and robot task allocation. It can also be used to design the paths and interlocks for an entire manufacturing line from the start.

The post New robot path planning software cuts weeks of programming appeared first on Engineering.com.